{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lv T"],"funding":["Shandong Provincial Postdoctoral Innovative Talents Support Program","Natural Science Foundation of Shandong Province","National Natural Science Foundation of China"],"pagination":["42103"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12658181"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["The genome of Penaeus vannamei is rich in short tandem repeats (STRs), occupying 18.96% of the genome, with 68.6% of loci showing high polymorphic information content, highlighting their potential as molecular markers. Accordingly, we performed an integrative GWAS leveraging STR, SNP, and InDel markers to identify 78 growth-associated loci, including 17 additional STRs compared with single-marker GWAS and six high-linkage regions containing metabolic, molting, and other growth-related genes. Four markers were validated in an independent population. In genomic prediction, STRs outperformed SNPs under the GBLUP model at low marker densities (20-50 loci), with accuracy gains up to 183%. GWAS-informed marker selection improved cross-population prediction performance, with STR-Top sets enhancin"],"journal":["Scientific reports"],"pubmed_title":["Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp."],"pmcid":["PMC12658181"],"funding_grant_id":["SDBX202302022","ZR2024QC192","32273129"],"pubmed_authors":["Xia Y","Fu Q","Liu J","Liu M","Tan J","Chen M","Cao J","Luan S","Kong J","Chen B","Meng X","Li X","Luo K","Dai P","Sui J","Qiang G","Lv T","Zhou H","Xing Q"],"additional_accession":[]},"is_claimable":false,"name":"Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.","description":"The genome of Penaeus vannamei is rich in short tandem repeats (STRs), occupying 18.96% of the genome, with 68.6% of loci showing high polymorphic information content, highlighting their potential as molecular markers. Accordingly, we performed an integrative GWAS leveraging STR, SNP, and InDel markers to identify 78 growth-associated loci, including 17 additional STRs compared with single-marker GWAS and six high-linkage regions containing metabolic, molting, and other growth-related genes. Four markers were validated in an independent population. In genomic prediction, STRs outperformed SNPs under the GBLUP model at low marker densities (20-50 loci), with accuracy gains up to 183%. GWAS-informed marker selection improved cross-population prediction performance, with STR-Top sets enhancin","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-06-08T04:49:51.544Z","creation":"2026-06-08T03:08:51.568Z"},"accession":"S-EPMC12658181","cross_references":{"pubmed":["41298594"],"doi":["10.1038/s41598-025-26048-3"]}}